Data filtering for the selection of major markers
Heatmaps that are based on data clustering display the overall profiles of the experimental values for the given samples. QCanvas provides a data-filtering option to selectively display data nodes satisfying a given threshold. In the example shown in Fig. 2C, data points with a 2-fold change (increase or decrease) in gene expression are selectively displayed. In many cases, a dataset includes experimental values and statistical confidence levels together. The option for data filtering in QCanvas is useful for analyzing patterns in the experimental data that are statistically significant. One can filter the heatmap profiles using statistical confidence data that are included in a separate file. In the example shown in Fig. 2D, the gene expression data are filtered based on the p-values for the fold-change. QCanvas can import two separate files together for simultaneous data clustering and filtering. The GUI menu for data filtering enables the pattern analysis to be performed easily, without the need for manual data processing or the use of scripting languages.